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    <title>Why Doesn't TETRAD?</title>
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        <td><h2><font color="#FFFFFF">Why Doesn't Tetrad...?</font></h2></td>
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<h3>Provide descriptive statistics?</h3>
<p> - Because those statistics can easily be obtained in Excel or Matlab</p>
<h3><br>
    Transform variables, e.g., by taking logs</h3>
<p> - Because this can be done in common commercial packages</p>
<h3><br>
    Do linear regression analysis?</h3>
<p> - Same answer.</p>
<h3><br>
    Use logistic regression or log-linear models?</h3>
<p> - These regression procedures could be valuable in estimating parameters in
    Bayes nets, but they require a sound search procedure for selecting interaction
    terms, and we haven't solved that yet.</p>
<h3><br>
    Do factor analysis?</h3>
<p> - Probably it should. For many problems, however, the latent variable search
    procedure in Tetrad is preferable.</p>
<h3><br>
    Deal with non-Normal distributions for continuous variables?</h3>
<p> -Relevant statistics are available only for Normal, Multinomial and Conditional
    Gaussian distribution families; the last should be included. </p>
<h3><br>
    Provide all of the models consistent with search output, instead of "CPDAGs,"
    PAGs" etc.</h3>
<p>- The models corresponding to a CPDAG could and perhaps should be provided,
    but their an infinite number of models consistent with a PAG, and your computer
    is finite.</p>
<h3><br>
    Provide Bayesain search procedures when there may be latent variables?</h3>
<p> - No consistent, computationally feasible, general algoirithms are known.</p>
<h3><br>
    Provide search procedures for cyclic (non-recursive) models with latent variables</h3>
<p> - No consistent search procedures are known.</p>
<h3><br>
    Provide search procedures for time series?</h3>
<p> - Bayes net search procedures can in principle be used for time series, but
    no practical, consistent, general search procedures are known. The search algorithms
    in Tetrad can be used to search for "simultaneous" causal relations after&nbsp;
    regression on lags. </p>
<h3><br>
    Provide provide search procedures to find a common model or models for two or
    more separate data sets?</h3>
<p>- If the variables in one data set are a subset of those in the other data
    set, a common model can be sought with the present version of Tetrad. If the
    data sets have entirely distinct variable sets, no principled search procedure
    for a common model is possible. If the data sets contain some common and some
    distinct variables, a sometimes useful principled search is possible, but adequate
    algorithms have not yet been developed.</p>
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